Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images.

Chest X-ray images are used in deep convolutional neural networks for the detection of COVID-19, the greatest human challenge of the 21st century. Robustness to noise and improvement of generalization are the major challenges in designing these networks. In this paper, we introduce a strategy for data augmentation using the determination of the type and value of noise density to improve the robustness and generalization of deep CNNs for COVID-19 detection.

Development of a colloidal gold-based immunochromatographic test strip for screening of microalbuminuria.

A rapid immunochromatography (ICG) assay based on antibody colloidal gold nanoparticles specific to human serum albumin (HSA) was developed, and its applications for primary screening of HSA in the urine were evaluated. A monoclonal antibody (MAb) specific to HSA was produced from cloned hybridoma cells (EMRC1) and used to develop an ICG strip. The nanocolloidal gold, with an average particle diameter of 20 nm, was synthesized and labeled MAb as the detection reagent.

Colloidal nanogold-based immunochromatographic strip test for the detection of digoxin toxicity.

Digoxin is widely used as a cardiac glycoside drug in the treatment of various heart conditions. Because it is a toxic drug, it should be regularly monitored in the serum of patients under treatment. In this study, colloidal nanogold is synthesized and the preparation of nanogold-labeled monoclonal antibody probe to digoxin is described under optimal conditions.